A network-based approach to coauthorship credit allocation

Jinseok Kim, Jana Diesner

Research output: Contribution to journalArticlepeer-review

Abstract

We introduce and evaluate a novel network-based approach for determining individual credit of coauthors in multi-authored papers. In the proposed model, coauthorship is conceptualized as a directed, weighted network, where authors transfer coauthorship credits among one another. We validate the model by fitting it to empirical data about authorship credits from economics, marketing, psychology, chemistry, and biomedicine. Also, we show that our model outperforms prior alternatives such as fractional, geometric, arithmetic, and harmonic counting in generating coauthorship credit allocations that approximate the empirical data. The results from the empirical evaluation as well as the model’s capability to be adapted to domains with different norms for how to order authors per paper make the proposed model a robust and flexible framework for studying substantive questions about coauthorship across domains.

Original languageEnglish (US)
Pages (from-to)587-602
Number of pages16
JournalScientometrics
Volume101
Issue number1
DOIs
StatePublished - Oct 2014

Keywords

  • Authorship credit
  • Bibliometrics
  • Coauthor networks
  • Coauthor order

ASJC Scopus subject areas

  • Social Sciences(all)
  • Computer Science Applications
  • Library and Information Sciences

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